# Interactive Imitation Learning of Bimanual Movement Primitives

arXiv: https://arxiv.org/abs/2210.16220 · HTML: https://mlsanity.com/paper/2210.16220/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Placed in Robot manipulation imitation learning, one of 13 directions in Offline RL and imitation learning from data.
- Builds on 12 of its 55 references that are in the map.
- First posted on arXiv 28 Oct 2022.

## Placed in

- Offline RL and imitation learning from data / [Robot manipulation imitation learning](https://mlsanity.com/offlinerl/robot-manipulation-imitation-learning/)

## Builds on (most cited first, 12 of 12)

- [An Algorithmic Perspective on Imitation Learning](https://mlsanity.com/paper/1811.06711/) (2018)
- [Scalable Variational Gaussian Process Classification](https://mlsanity.com/paper/1411.2005/) (2014)
- [Mat'ern Gaussian processes on Riemannian manifolds](https://mlsanity.com/paper/2006.10160/) (2020)
- [Deep Imitation Learning for Bimanual Robotic Manipulation](https://mlsanity.com/paper/2010.05134/) (2020)
- [Dynamic Movement Primitives in Robotics: A Tutorial Survey](https://mlsanity.com/paper/2102.03861/) (2021)
- [Kernelized Movement Primitives](https://mlsanity.com/paper/1708.08638/) (2017)
- [Learning Multi-Arm Manipulation Through Collaborative Teleoperation](https://mlsanity.com/paper/2012.06738/) (2020)
- [ILoSA: Interactive Learning of Stiffness and Attractors](https://mlsanity.com/paper/2103.03099/) (2021)
- [Learning from demonstration with model-based Gaussian process](https://mlsanity.com/paper/1910.05005/) (2019)
- [Learning to Pick at Non-Zero-Velocity from Interactive Demonstrations](https://mlsanity.com/paper/2110.04534/) (2021)
- [Collaborative Bimanual Manipulation Using Optimal Motion Adaptation and Interaction Control](https://mlsanity.com/paper/2206.00528/) (2022)
- [Solving Robot Assembly Tasks by Combining Interactive Teaching and Self-Exploration](https://mlsanity.com/paper/2209.11530/) (2022)

## Built on by (most cited first, 18 of 18)

- [RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation](https://mlsanity.com/paper/2410.07864/) (2024)
- [Stabilize to Act: Learning to Coordinate for Bimanual Manipulation](https://mlsanity.com/paper/2309.01087/) (2023)
- [Bi-ACT: Bilateral Control-Based Imitation Learning via Action Chunking with Transformer](https://mlsanity.com/paper/2401.17698/) (2024)
- [Bi-VLA: Vision-Language-Action Model-Based System for Bimanual Robotic Dexterous Manipulations](https://mlsanity.com/paper/2405.06039/) (2024)
- [VoxAct-B: Voxel-Based Acting and Stabilizing Policy for Bimanual Manipulation](https://mlsanity.com/paper/2407.04152/) (2024)
- [ScrewMimic: Bimanual Imitation from Human Videos with Screw Space Projection](https://mlsanity.com/paper/2405.03666/) (2024)
- [Bi-KVIL: Keypoints-based Visual Imitation Learning of Bimanual Manipulation Tasks](https://mlsanity.com/paper/2403.03270/) (2024)
- [AnyBimanual: Transferring Unimanual Policy for General Bimanual Manipulation](https://mlsanity.com/paper/2412.06779/) (2024)
- [RationalVLA: A Rational Vision-Language-Action Model with Dual System](https://mlsanity.com/paper/2506.10826/) (2025)
- [A Comparison of Imitation Learning Algorithms for Bimanual Manipulation](https://mlsanity.com/paper/2408.06536/) (2024)
- [DABI: Evaluation of Data Augmentation Methods Using Downsampling in Bilateral Control-Based Imitation Learning with Images](https://mlsanity.com/paper/2410.04370/) (2024)
- [D-CODA: Diffusion for Coordinated Dual-Arm Data Augmentation](https://mlsanity.com/paper/2505.04860/) (2025)
- [Use the Force, Bot! -- Force-Aware ProDMP with Event-Based Replanning](https://mlsanity.com/paper/2409.11144/) (2024)
- [Towards a Generalizable Bimanual Foundation Policy via Flow-based Video Prediction](https://mlsanity.com/paper/2505.24156/) (2025)
- [Mastering Contact-rich Tasks by Combining Soft and Rigid Robotics with Imitation Learning](https://mlsanity.com/paper/2410.07787/) (2024)
- [CUBic: Coordinated Unified Bimanual Perception and Control Framework](https://mlsanity.com/paper/2605.13452/) (2026)
- [AsymDex: Asymmetry and Relative Coordinates for RL-based Bimanual Dexterity](https://mlsanity.com/paper/2411.13020/) (2024)
- [JAMB: Joint Action-Motion Diffusion for Bimanual Manipulation](https://mlsanity.com/paper/2609.25322/) (2026)

## Abstract (arXiv)

Performing bimanual tasks with dual robotic setups can drastically increase the impact on industrial and daily life applications. However, performing a bimanual task brings many challenges, like synchronization and coordination of the single-arm policies. This article proposes the Safe, Interactive Movement Primitives Learning (SIMPLe) algorithm, to teach and correct single or dual arm impedance policies directly from human kinesthetic demonstrations. Moreover, it proposes a novel graph encoding of the policy based on Gaussian Process Regression (GPR) where the single-arm motion is guaranteed to converge close to the trajectory and then towards the demonstrated goal. Regulation of the robot stiffness according to the epistemic uncertainty of the policy allows for easily reshaping the motion with human feedback and/or adapting to external perturbations. We tested the SIMPLe algorithm on a real dual-arm setup where the teacher gave separate single-arm demonstrations and then successfully synchronized them only using kinesthetic feedback or where the original bimanual demonstration was locally reshaped to pick a box at a different height.